Predictive Module Degradation and Failure Identification Solution

A significant challenge to the larger scale adoption and investment in distributed photovoltaic (PV) generation is the inherent annual operation and maintenance (O&M) cost due to degradation and eventual failure of PV modules. There are numerous reasons that a PV module might experience reduced performance or complete failure, but the end result is that a significant amount of the costs associated with a PV installation are either directly or indirectly tied to module degradation and failure. The acquisition, processing, and utilization the elimination and mitigation of degradation mechanisms and failure modes in PV modules should be the ultimate goal in turning PV into a truly bankable, risk averse energy resource. This team proposes to develop an easily adoptable hybrid light/dark I-V measurement integrated power electronics solution and data analysis solution that can provide module-level diagnostic information and prognostic information about the health of specific modules. Through an alert system operators can be notified of accelerated degradation and potential failures before a catastrophic failure occurs, ultimately providing critical data which can allow for lower cost and lower risk PV adoption. These module-level diagnostics/prognostics can reduce and even eliminate module failures in the field while significantly reducing O&M costs and increasing system energy yield (kWh/kWp). The proposed technology has the potential to be relatively easily integrated into existing power conversion unit designed (e.g. micro-inverters, micro-converters, string-converters, or even as on-board module electronics) at a low cost by adding the hybrid light/dark I-V power sampling circuit and implementing the diagnostics functions in the embedded control software, as opposed to requiring the addition of a costly new device or hardware to a system. With this knowledge, the future failures of modules can be predicted, analyzed, and subverted in a cost effective manner, reducing the high costs associated with in-field failures in the PV industry.